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The entire process is\nvisualized in real-time through a dynamic **Streamlit Dashboard**.\n\n🔗 **[Live Demo](https://git-repo-bug-fixer.streamlit.app/)**\n\n> ⚠️ **Note:** If the app shows a loading screen on first visit, please\n> wait 60 seconds — it auto-wakes from sleep mode. To run the pipeline,\n> you will need your own **GitHub Personal Access Token**, a **Gemini** or\n> **OpenRouter API Key**, and a **target GitHub Repository URL** — enter\n> all three directly in the dashboard before starting.\n\n![Project Poster](assets/github-repository-multi-agent-bug-fixer.png)\n\n---\n\n## 🚀 Features\n\n* **Multi-Agent Collaboration:** Sequential coordination between 4 specialized agents:\n  1. **Collector Agent:** Fetches repository structure, files, commits, and issue descriptions.\n  2. **Analyzer Agent:** Performs static analysis (Python AST checking, JavaScript evaluations) and reasons to identify critical bugs.\n  3. **Fixer Agent:** Creates a bug-fix branch, applies precise patches, and pushes them to GitHub.\n  4. **Reviewer Agent:** Validates changes, runs regressions, and automatically raises a Pull Request on GitHub.\n* **Interactive Dashboard:** Run audits, check real-time terminal logs, and inspect outputs in structured tabs.\n* **Dual LLM Provider Support:** Run directly using Google Gemini models (e.g. `gemini-3.1-flash-lite`, `gemini-2.5-pro`) or OpenRouter models (e.g. Qwen, LLaMA).\n* **🎨 Premium Dark Theme:** Sleek dark-mode aesthetic with rounded glassmorphic elements and high-contrast readability.\n* **🔧 API Diagnostics Utility:** Diagnose GitHub Access Permissions and query available Gemini models before starting audits.\n* **♻️ Auto-Clean & Safety:** Automatically cleans up intermediate outputs on new runs, with manual override controls.\n* **Robust Tool Orchestration:** Scripts are self-healing (downstream agents automatically run preceding dependency scripts if intermediate files are missing).\n\n---\n\n## 🛠️ Prerequisites\n\n* **Python 3.11** installed on your system.\n* A **GitHub Personal Access Token (PAT)** with `repo` scope permissions.\n* A **Google Gemini API Key** (from Google AI Studio) or an **OpenRouter API Key**.\n\n---\n\n## ⚙️ Installation & Setup\n\nFollow these steps to set up the project locally:\n\n### 1. Clone the Repository\n```bash\ngit clone <repository-url>\ncd github-repo-multi-agent-bug-fixer\n```\n\n### 2. Configure Environment Variables\nCopy the example configuration file and rename it to `.env`:\n```bash\ncp .env.example .env\n```\nOpen the `.env` file in your editor and fill in your keys:\n```env\nGITHUB_PERSONAL_ACCESS_TOKEN=your_actual_github_personal_access_token\nGEMINI_API_KEY=your_actual_gemini_api_key\n\n# Optional: If you intend to use OpenRouter instead of Google Gemini direct API\nOPENROUTER_API_KEY=your_actual_openrouter_api_key\n```\n\n\n### 3. Setup MCP Configuration (Optional for AI Assistants)\nIf you are developing this project using an AI coding assistant like **Antigravity** (which supports Model Context Protocol), you can enable the assistant to interact directly with your GitHub repositories.\n\nCopy the example MCP configuration file and rename it to `.agents/mcp_config.json`:\n```bash\ncp .agents/mcp_config.json.example .agents/mcp_config.json\n```\nOpen `.agents/mcp_config.json` and replace `YOUR_GITHUB_PERSONAL_ACCESS_TOKEN_HERE` with your actual token.\n\n### 4. Create a Virtual Environment & Activate It\n* **Windows (PowerShell):**\n  ```powershell\n  python -m venv .venv\n  .venv\\Scripts\\Activate.ps1\n  ```\n* **macOS / Linux:**\n  ```bash\n  python3 -m venv .venv\n  source .venv/bin/activate\n  ```\n\n### 5. Install Dependencies\n```bash\npip install -r requirements.txt\n```\n\n---\n\n## 🖥️ Running the Application\n\nTo launch the Streamlit dashboard, run:\n```bash\nstreamlit run app.py\n```\n\nThis will automatically open the application interface in your default web browser (usually at `http://localhost:8501`).\n\n---\n\n## 📁 Project Structure\n\n```\n├── .agents/                    # Agent specifications & configurations\n│   ├── agents/                 # Markdown prompts for agent backstories\n│   │   ├── collector-agent.md  # Backstory and profile for the Collector Agent\n│   │   ├── analyzer-agent.md   # Backstory and profile for the Analyzer Agent\n│   │   ├── fixer-agent.md      # Backstory and profile for the Fixer Agent\n│   │   └── reviewer-agent.md   # Backstory and profile for the Reviewer Agent\n│   └── skills/                 # Markdown prompts for agent task goals\n│       ├── collector-skill/    # Task goals & collector instructions (SKILL.md)\n│       ├── analyzer-skill/     # Task goals & static analyzer instructions (SKILL.md)\n│       ├── fixer-skill/        # Task goals & fixer sandbox instructions (SKILL.md)\n│       └── reviewer-skill/     # Task goals & PR validation instructions (SKILL.md)\n├── .streamlit/                 # Streamlit application configurations\n│   └── config.toml             # Custom theme and page settings\n├── assets/                     # Visual architecture diagrams and media\n├── scripts/                    # Actionable scripts wrapped by CrewAI\n│   ├── collector.py            # Pulls codebase & metadata from GitHub\n│   ├── analyzer.py             # Run AST checks and highlights logic bugs\n│   ├── fixer.py                # Patches source files dynamically in-memory\n│   └── reviewer.py             # Performs LLM QA review and commits changes to GitHub upon approval\n├── AGENTS.md                   # Project constraints and agent workspace rules\n├── CHANGELOG.md                # Detailed history of project features and optimizations\n├── agent_runner.py             # CrewAI orchestration layer\n├── app.py                      # Streamlit interactive dashboard UI\n├── requirements.txt            # Project python dependencies\n├── .env.example                # Template configuration file\n└── README.md                   # This documentation file\n```\n","readmeExcerpt":"🤖 GitHub Repository Multi-Agent Bug Fixer $1 🏆 **Capstone Project** — Kaggle's 5-Day AI Agents: Intensive Vibe Coding Course with Google (July 2026) An autonomous 4-agent system powered by **CrewAI** and **Google Gemini** that audits a GitHub repository, identifies bugs, applies minimal code patches, and submits a Pull Request for review. 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